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Introduction: Diabetic retinopathy (DR) detection is made easy with the use of a fundus camera. The evidence of the use of a fundus camera for DR detection in non-mydriatic conditions with limited technical challenges is scarce. This is a pilot study that evaluates the performance of the Oivi fundus camera (Oivi AS, Oslo, Norway), a novel non-mydriatic tabletop fundus camera for DR detection using a single-field, macula-centered imaging approach. Its diagnostic accuracy was compared with that of a standard reference device, the Topcon NW400 fundus camera (Topcon Corporation, Tokyo, Japan).
Methods: A total of 243 subjects with diabetes mellitus (DM) were recruited. Non-mydriatic macula-centered images were captured using both cameras. Two ophthalmologists independently graded the deidentified images for image quality and DR stage. Discrepancies between their assessments were adjudicated by consensus after review by a senior ophthalmologist. The senior ophthalmologist's grading of images from the standard camera images served as the ground truth for comparative analysis. Inter-modality agreement was evaluated using linear weighted kappa (κ) correlation.
Results: DR was detected in 23% of patients using the standard reference camera (12% of eyes) and in 23.86% using the tabletop camera (12.6%). Identification of moderate non-proliferative diabetic retinopathy (NPDR) (7.2%), severe NPDR (0.4%), and proliferative diabetic retinopathy (PDR) (1.23%) was similar between the two cameras, although not always in the same eyes. The inter-modality agreement (k) for DR was 0.927 (95% CI: 0.88-0.97) (almost perfect). The tabletop camera showed a sensitivity of 92.98% (95% CI, 83-98.05%) and a specificity of 99.47% (95% CI, 98.10-99.94%) for DR. The percentage of usable images was 92.3% with the standard reference camera and 95.2% with the tabletop camera.
Conclusions: This study provides preliminary evidence that the novel tabletop Oivi fundus camera may offer comparable performance to standard non-mydriatic devices for DR detection in a single-field strategy. Its portability and usability under mesopic conditions suggest potential value for point-of-care screening. Further large-scale studies are warranted to validate these findings and explore their role in screening programs.
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http://dx.doi.org/10.7759/cureus.88198 | DOI Listing |
JMIR Med Inform
September 2025
Global Health Economics Centre, Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Background: Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions.
Objective: This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings.
Entropy (Basel)
August 2025
College of Computer Science and Technology, Jilin University, Changchun 130012, China.
Retinal vessel segmentation plays a crucial role in diagnosing various retinal and cardiovascular diseases and serves as a foundation for computer-aided diagnostic systems. Blood vessels in color retinal fundus images, captured using fundus cameras, are often affected by illumination variations and noise, making it difficult to preserve vascular integrity and posing a significant challenge for vessel segmentation. In this paper, we propose HM-Mamba, a novel hierarchical multi-scale Mamba-based architecture that incorporates tubular structure-aware convolution to extract both local and global vascular features for retinal vessel segmentation.
View Article and Find Full Text PDFOphthalmol Retina
August 2025
Department of Ophthalmology, Affiliated Changshu Hospital of Nantong University, Changshu City, Jiangsu Province, China.
J Ophthalmic Inflamm Infect
August 2025
Department of Ophthalmology, Faculty of Medicine, Academic Assembly, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan.
Background: Vogt-Koyanagi-Harada (VKH) disease affects visual function, but the recovery process of color vision remains incompletely understood. This study aimed to assess color vision recovery in VKH using cone contrast testing and explore its relationship with cone cell density measured using adaptive optics imaging.
Methods: Twenty-two eyes of 11 patients with VKH were evaluated at baseline (serous retinal detachment resolution) and at 3, 6, and 12 months post-treatment.
Ophthalmology
August 2025
Department of Ophthalmology, Emory University School of Medicine, Atlanta, Georgia, USA; Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA. Electronic address:
Objective: To compare our institution's emergency department and inpatient neuro-ophthalmology consultation patterns from 2024 (after implementation of non-mydriatic ocular imaging in our general emergency department) to the 494 neuro-ophthalmology consultations seen in 2022 (prior to implementation of the camera).
Design: Prospective observational study SUBJECTS: Consecutive patients seen as emergency department or inpatient neuro-ophthalmology consultations at a single large urban academic medical center.
Methods: Systematic collection of consecutive emergency department and inpatient neuro-ophthalmology consultations at one academic center in 2024 and comparison of results with data prospectively obtained during year 2022.